The transformative potential of artificial intelligence in solid organ transplantation.

Solid organ transplantation confronts numerous challenges ranging from donor organ shortage to post-transplant complications. Here, we provide an overview of the latest attempts to address some of these challenges using artificial intelligence (AI). We delve into the application of machine learning in pretransplant evaluation, predicting transplant rejection, and post-operative patient outcomes. By providing a comprehensive overview of AI's current impact, this review aims to inform clinicians, researchers, and policy-makers about the transformative power of AI in enhancing solid organ transplantation and facilitating personalized medicine in transplant care.

Interneuron FGF13 regulates seizure susceptibility via a sodium channel-independent mechanism.

Developmental and Epileptic Encephalopathies (DEEs), a class of devastating neurological disorders characterized by recurrent seizures and exacerbated by disruptions to excitatory/inhibitory balance in the brain, are commonly caused by mutations in ion channels. Disruption of, or variants in, FGF13 were implicated as causal for a set of DEEs, but the underlying mechanisms were clouded because FGF13 is expressed in both excitatory and inhibitory neurons, FGF13 undergoes extensive alternative splicing producing multiple isoforms with distinct functions, and the overall roles of FGF13 in neurons are incompletely cataloged. To overcome these challenges, we generated a set of novel cell type-specific conditional knockout mice. Interneuron-targeted deletion of Fgf13 led to perinatal mortality associated with extensive seizures and impaired the hippocampal inhibitory/excitatory balance while excitatory neuron-targeted deletion of Fgf13 caused no detectable seizures and no survival deficits. While best studied as a voltage-gated sodium channel (Nav) regulator, we observed no effect of Fgf13 ablation in interneurons on Navs but rather a marked reduction in K+ channel currents. Re-expressing different Fgf13 splice isoforms could partially rescue deficits in interneuron excitability and restore K+ channel current amplitude. These results enhance our understanding of the molecular mechanisms that drive the pathogenesis of Fgf13-related seizures and expand our understanding of FGF13 functions in different neuron subsets.

Lung CT harmonization of paired reconstruction kernel images using generative adversarial networks.

BACKGROUND: The kernel used in CT image reconstruction is an important factor that determines the texture of the CT image. Consistency of reconstruction kernel choice is important for quantitative CT-based assessment as kernel differences can lead to substantial shifts in measurements unrelated to underlying anatomical structures. PURPOSE: In this study, we investigate kernel harmonization in a multi-vendor low-dose CT lung cancer screening cohort and evaluate our approach's validity in quantitative CT-based assessments. METHODS: Using the National Lung Screening Trial, we identified CT scan pairs of the same sessions with one reconstructed from a soft tissue kernel and one from a hard kernel. In total, 1000 pairs of five different paired kernel types (200 each) were identified. We adopt the pix2pix architecture to train models for kernel conversion. Each model was trained on 100 pairs and evaluated on 100 withheld pairs. A total of 10 models were implemented. We evaluated the efficacy of kernel conversion based on image similarity metrics including root mean squared error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM) as well as the capability of the models to reduce measurement shifts in quantitative emphysema and body composition measurements. Additionally, we study the reproducibility of standard radiomic features for all kernel pairs before and after harmonization. RESULTS: Our approach effectively converts CT images from one kernel to another in all paired kernel types, as indicated by the reduction in RMSE (p < 0.05) and an increase in the PSNR (p < 0.05) and SSIM (p < 0.05) for both directions of conversion for all pair types. In addition, there is an increase in the agreement for percent emphysema, skeletal muscle area, and subcutaneous adipose tissue (SAT) area for both directions of conversion. Furthermore, radiomic features were reproducible when compared with the ground truth features. CONCLUSIONS: Kernel conversion using deep learning reduces measurement variation in percent emphysema, muscle area, and SAT area.

Evaluation of Mean Shift, ComBat, and CycleGAN for Harmonizing Brain Connectivity Matrices Across Sites.

Connectivity matrices derived from diffusion MRI (dMRI) provide an interpretable and generalizable way of understanding the human brain connectome. However, dMRI suffers from inter-site and between-scanner variation, which impedes analysis across datasets to improve robustness and reproducibility of results. To evaluate different harmonization approaches on connectivity matrices, we compared graph measures derived from these matrices before and after applying three harmonization techniques: mean shift, ComBat, and CycleGAN. The sample comprises 168 age-matched, sex-matched normal subjects from two studies: the Vanderbilt Memory and Aging Project (VMAP) and the Biomarkers of Cognitive Decline Among Normal Individuals (BIOCARD). First, we plotted the graph measures and used coefficient of variation (CoV) and the Mann-Whitney U test to evaluate different methods' effectiveness in removing site effects on the matrices and the derived graph measures. ComBat effectively eliminated site effects for global efficiency and modularity and outperformed the other two methods. However, all methods exhibited poor performance when harmonizing average betweenness centrality. Second, we tested whether our harmonization methods preserved correlations between age and graph measures. All methods except for CycleGAN in one direction improved correlations between age and global efficiency and between age and modularity from insignificant to significant with p-values less than 0.05.

Vertical transmission and prevalence of white spot syndrome virus (WSSV) in the wild spawning population of the Indian white shrimp, Penaeus indicus.

White spot disease, caused by white spot syndrome virus (WSSV), has historically been the most devastating disease in shrimp aquaculture industry across the world. The mode of virus transmission is the most crucial stage in the dynamics and management of virus infection. This study explored the mechanism of vertical transmission of WSSV in Indian white shrimp, Penaeus indicus, potential native species for domestication and genetic improvement, using quantitative real time PCR (q RT PCR), light and electron microscopy, and in situ hybridization. Wild brooders of P. indicus (n = 2576) were sampled along the South east coast of India, during 2016 to 2021. Of these âˆ¼ 58 % of the brooders were positive for WSSV, and almost 50 % of infected wild brooders were at the various stages of reproductive maturation. WSSV-PCR positive brooders (n = 200) were analysed for vertical WSSV transmission. The q RT PCR studies of reproductive tissues revealed that 61 % (n = 13) of spermatophore, 54 % (n = 28) of immature ovaries and 48 % (n = 27) of ripe ovaries were infected with WSSV. The lowest level of infection was recorded in females with ripe ovaries (6.84 × 101 ± 9.79 × 100 ng genomic DNA) followed by fertilized eggs (1.59 × 102 ± 3.69 × 101 ng genomic DNA), and larvae (nauplius and zoea). The histology of gravid females with high WSSV copies showed pyknotic and karyorrhectic germinal vesicle with degenerated cortical rods. Conversely, the gravid females with low WSSV copies showed fully developed ovary without characteristic signs of WSSV infection. Transmission electron microscopic studies clearly established the presence of WSSV particles in both ovaries and spermatophores. When subjected to in situ hybridization, WSSV-specific signals were observed in connective tissues of spermatophore, although gravid ovary and fertilized eggs were failed to produce WSSV specific signals. The present study provides the first molecular and histological evidence for trans-ovarian vertical transmission of WSSV. Development of disease-free base population being the cornerstone and first step in establishing the breeding program, the present findings could be a basis for development of such programs.

Characterizing patterns of DTI variance in aging brains.

Background: As large analyses merge data across sites, a deeper understanding of variance in statistical assessment across the sources of data becomes critical for valid analyses. Diffusion tensor imaging (DTI) exhibits spatially varying and correlated noise, so care must be taken with distributional assumptions. Purpose: We characterize the role of physiology, subject compliance, and the interaction of subject with the scanner in the understanding of DTI variability, as modeled in spatial variance of derived metrics in homogeneous regions. Methods: We analyze DTI data from 1035 subjects in the Baltimore Longitudinal Study of Aging (BLSA), with ages ranging from 22.4 to 103 years old. For each subject, up to 12 longitudinal sessions were conducted. We assess variance of DTI scalars within regions of interest (ROIs) defined by four segmentation methods and investigate the relationships between the variance and covariates, including baseline age, time from the baseline (referred to as "interval"), motion, sex, and whether it is the first scan or the second scan in the session. Results: Covariate effects are heterogeneous and bilaterally symmetric across ROIs. Inter-session interval is positively related (p ≪ 0.001) to FA variance in the cuneus and occipital gyrus, but negatively (p ≪ 0.001) in the caudate nucleus. Males show significantly (p ≪ 0.001) higher FA variance in the right putamen, thalamus, body of the corpus callosum, and cingulate gyrus. In 62 out of 176 ROIs defined by the Eve type-1 atlas, an increase in motion is associated (p < 0.05) with a decrease in FA variance. Head motion increases during the rescan of DTI (Δµ = 0.045 millimeters per volume). Conclusions: The effects of each covariate on DTI variance, and their relationships across ROIs are complex. Ultimately, we encourage researchers to include estimates of variance when sharing data and consider models of heteroscedasticity in analysis. This work provides a foundation for study planning to account for regional variations in metric variance.

Age-related Muscle Fat Infiltration in Lung Screening Participants: Impact of Smoking Cessation.

Rationale: Skeletal muscle fat infiltration progresses with aging and is worsened among individuals with a history of cigarette smoking. Many negative impacts of smoking on muscles are likely reversible with smoking cessation. Objectives: To determine if the progression of skeletal muscle fat infiltration with aging is altered by smoking cessation among lung cancer screening participants. Methods: This was a secondary analysis based on the National Lung Screening Trial. Skeletal muscle attenuation in Hounsfield unit (HU) was derived from the baseline and follow-up low-dose CT scans using a previously validated artificial intelligence algorithm. Lower attenuation indicates greater fatty infiltration. Linear mixed-effects models were constructed to evaluate the associations between smoking status and the muscle attenuation trajectory. Measurements and Main Results: Of 19,019 included participants (age: 61 years, 5 [SD]; 11,290 males), 8,971 (47.2%) were actively smoking cigarettes. Accounting for body mass index, pack-years, percent emphysema, and other confounding factors, actively smoking predicted a lower attenuation in both males (ß0 =-0.88 HU, P<.001) and females (ß0 =-0.69 HU, P<.001), and an accelerated muscle attenuation decline-rate in males (ß1=-0.08 HU/y, P<.05). Age-stratified analyses indicated that the accelerated muscle attenuation decline associated with smoking likely occurred at younger age, especially in females. Conclusions: Among lung cancer screening participants, active cigarette smoking was associated with greater skeletal muscle fat infiltration in both males and females, and accelerated muscle adipose accumulation rate in males. These findings support the important role of smoking cessation in preserving muscle health.

Exploration of Coumarin Derivative: Experimental and Computational Modeling for Dipole Moment Estimation and Thermal Sensing Application.

The Optical properties of the FBTC (1-((4-((5-chlorobenzo[d]oxazol-2-ylthio)methyl)-1H-1,2,3-triazol-1-yl)methyl)-3H-benzo[f]chromen-3-one) molecule were studied experimentally and theoretically. The spectra of absorption and fluorescence were recorded in various solvents to explore their Solvatochromic behavior and dipole moment at room temperature. To determine the ground and excited state of dipole moment experimentally and theoretically, we employed different Solvatochromic techniques, including microscopic solvent polarity functions developed by Lippert, Bakhshiev, Kawaski-Chamma-Viallet, and Reichardt's, as well as density functional theory (DFT) and time-dependent density functional theory (TD-DFT) methods. The stability of the excited state dipole moment in FBTC is higher. Using prime functional, FBTC was optimized in its ground state, and its HOMO (Highest Occupied Molecular Orbital) and LUMO (Lowest Unoccupied Molecular Orbital), energies were estimated. These values were then compared with those obtained through cyclic voltammetry. Based on the HOMO and LUMO values given, we calculated the global reactivity parameter and energy gap, which was found to be low at 3.77 eV. This study also includes an estimation of electron absorption energies and oscillator strength. Natural population analysis (NPA), Milliken atomic charge, and molecular electrostatic potential (MESP) map are correlated. In addition, FBTC exhibited exceptional physiological temperature sensing behaviour from 20 °C -65 °C with high relative sensitivity and firm stability. Hence these results confirm that FBTC is a potential candidate for photonic devices and it's also applicable in optical temperature sensing.

Psychosocial preparedness among homeless people: A study from an urban rehabilitation center in South India.

Background: Homeless people have difficulties in their basic necessities such as food, clothing, and shelter and they are prone to physical abuse and assault. Homeless mentally ill persons are found to have unhealed injuries and they lack help-seeking behavior, which leads to further deterioration of physical and mental health. In view of the alarming increase in this marginalized population, there is a need to understand their psychosocial needs and enhance their well-being and quality of life. The study aims to understand the psychosocial preparedness of homeless people admitted to a relief and rehabilitation center in Bengaluru. Methods: The study followed a descriptive research design with 90 participants (10% of total inmates), 45 participants each falling under the categories of homeless persons with mental illness (HMI) and homeless persons without mental illness (NMI), selected using a simple random sampling method. A semi-structured interview schedule was used for data collection. Statistics procedures used frequency distribution, mean, median, and standard deviations and inferential statistics such as the Chi-square test. Results: The results of the study show that the majority of the respondents (56% in HMI and 73% in NMI) were male, 62% in HMI and 60% in NMI were literate, 60% in HMI and 86.66% in NMI were employed before institutionalization, 73% in HMI and 69% in NMI belonged to nuclear family. The study also shows that the majority of the HMI (56%) had no plans to start work; however, the majority of the NMI (49%) had plans to start work. Mean scores indicate persons with mental illness have more psychosocial preparedness than persons without mental illness. Discussion: The results showed that there was no significant difference between the mean level of psychosocial preparedness among persons with mental illness and persons without mental illness.

On the significance of membrane unfolding in mechanosensitive cell spreading: Its individual and synergistic effects.

Mechanosensitivity of cell spread area to substrate stiffness has been established both through experiments and different types of mathematical models of varying complexity including both the mechanics and biochemical reactions in the cell. What has not been addressed in previous mathematical models is the role of cell membrane dynamics on cell spreading, and an investigation of this issue is the goal of this work. We start with a simple mechanical model of cell spreading on a deformable substrate and progressively layer mechanisms to account for the traction dependent growth of focal adhesions, focal adhesion induced actin polymerization, membrane unfolding/exocytosis and contractility. This layering approach is intended to progressively help in understanding the role each mechanism plays in reproducing experimentally observed cell spread areas. To model membrane unfolding we introduce a novel approach based on defining an active rate of membrane deformation that is dependent on membrane tension. Our modeling approach allows us to show that tension-dependent membrane unfolding plays a critical role in achieving the large cell spread areas experimentally observed on stiff substrates. We also demonstrate that coupling between membrane unfolding and focal adhesion induced polymerization works synergistically to further enhance cell spread area sensitivity to substrate stiffness. This enhancement has to do with the fact that the peripheral velocity of spreading cells is associated with contributions from the different mechanisms by either enhancing the polymerization velocity at the leading edge or slowing down of the retrograde flow of actin within the cell. The temporal evolution of this balance in the model corresponds to the three-phase behavior observed experimentally during spreading. In the initial phase membrane unfolding is found to be particularly important.

Long-term Effects of a Collaborative Care Model on Metabolic Outcomes and Depressive Symptoms: 36-Month Outcomes from the INDEPENDENT Intervention.

BACKGROUND: Collaborative care (CC) is a multicomponent team-based approach to providing mental health care with systematic integration into outpatient medical settings. The 12-month INDEPENDENT CC intervention improved joint disease control measures in patients with both depression and diabetes at 12 and 24 months following randomization. OBJECTIVE: This study investigated the durability of intervention effects on patient outcomes at 36 months following randomization. PARTICIPANTS: Adult patients with poorly controlled T2D and depression in India randomized to CC or usual care. DESIGN: Post hoc analyses of between-group differences in patient outcomes at 36 months post-randomization (N = 331) and maintenance of outcomes from 12 to 36 months (N = 314). MAIN MEASURES: We evaluated combined risk factor improvement since baseline, defined as ≥ 50.0% reduction in Symptom Checklist Depression Scale (SCL-20) scores along with reduction of at least 0.5 percentage point hemoglobin A1C, 5 mmHg systolic blood pressure, or 10 mg/dL low-density lipoprotein cholesterol. Improvements in single risk factors were also examined. KEY RESULTS: There were no between-group differences in improvements since baseline in multiple or single risk factors at 36 months. Patients in the CC group with improved outcomes at 12 months were more likely to maintain a ≥ 50.0% reduction since baseline in SCL-20 scores (CC [54.9%] vs. UC [40.9%]; RR: 1.27 [95% CI: 1.04, 1.56]) and 0.5 percentage point reduction since baseline in hemoglobin A1C (CC [31.9%] vs. UC [19.5%]; RR: 1.64 [95% CI: 1.11, 2.41]) at 36 months. CONCLUSIONS: While improvements since baseline in patient outcomes did not differ between the collaborative care and usual care groups at 36 months, patients who received CC were more likely to maintain improvements in depressive symptoms and glucose levels at 36 months if they had achieved these improvements at the end of active intervention. TRIAL REGISTRATION NUMBER: NCT02022111.

Coumarin Triazoles as Potential Antimicrobial Agents.

Currently, in hospitals and community health centers, microbial infections are highly common diseases and are a leading cause of death worldwide. Antibiotics are generally used to fight microbial infections; however, because of the abuse of antibiotics, microbes have become increasingly more resistant to most of them. Therefore, medicinal chemists are constantly searching for new or improved alternatives to combat microbial infections. Coumarin triazole derivatives displayed a variety of therapeutic applications, such as antimicrobial, antioxidant, and anticancer activities. This review summarizes the advances of coumarin triazole derivatives as potential antimicrobial agents covering articles published from 2006 to 2022.

Cost-Effectiveness of a Collaborative Care Model Among Patients With Type 2 Diabetes and Depression in India.

OBJECTIVE: To assess the cost-effectiveness of collaborative versus usual care in adults with poorly controlled type 2 diabetes and depression in India. RESEARCH DESIGN AND METHODS: We performed a within-trial cost-effectiveness analysis of a 24-month parallel, open-label, pragmatic randomized clinical trial at four urban clinics in India from multipayer and societal perspectives. The trial randomly assigned 404 patients with poorly controlled type 2 diabetes (HbA1c ≥8.0%, systolic blood pressure ≥140 mmHg, or LDL cholesterol ≥130 mg/dL) and depressive symptoms (9-item Patient Health Questionnaire score ≥10) to collaborative care (support from nonphysician care coordinators, electronic registers, and specialist-supported case review) for 12 months, followed by 12 months of usual care or 24 months of usual care. We calculated incremental cost-effectiveness ratios (ICERs) in Indian rupees (INR) and international dollars (Int'l-$) and the probability of cost-effectiveness using quality-adjusted life-years (QALYs) and depression-free days (DFDs). RESULTS: From a multipayer perspective, collaborative care costed an additional INR309,558 (Int'l-$15,344) per QALY and an additional INR290.2 (Int'l-$14.4) per DFD gained compared with usual care. The probability of cost-effectiveness was 56.4% using a willingness to pay of INR336,000 (Int'l-$16,654) per QALY (approximately three times per-capita gross domestic product). The willingness to pay per DFD to achieve a probability of cost-effectiveness >95% was INR401.6 (Int'l-$19.9). From a societal perspective, cost-effectiveness was marginally lower. In sensitivity analyses, integrating collaborative care in clinical workflows reduced incremental costs by ∼47% (ICER 162,689 per QALY, cost-effectiveness probability 89.4%), but cost-effectiveness decreased when adjusting for baseline values. CONCLUSIONS: Collaborative care for patients with type 2 diabetes and depression in urban India can be cost-effective, especially when integrated in clinical workflows. Long-term cost-effectiveness might be more favorable. Scalability across lower- and middle-income country settings depends on heterogeneous contextual factors.

Experimental and Theoretical Spectroscopic Investigation on Coumarin Based Derivatives for Non-Linear Optoelectronics Application.

The spectral properties of MBTC (4-((4-((Benzo[d]oxazol-2-ylthio)methyl)-1H-1,2,3-triazol-1-yl)methyl)-7-methoxy-2H-chromen-2-one), CBTC (4-((4(((5Chlorobenzo[d]oxazol-2-yl)thio)methyl)-1H-1,2,3-triazol-1-yl)methyl)-2H-benzo[h]chromen-2-one) and TBTC (4-((4-((Benzo[d]oxazol-2-ylthio)methyl)-1H-1,2,3-triazol-1-yl)methyl)6(tertbutyl)2Hchromen-2-one) were studied in series of solvents with different polarity at room temperature to explore their solvatochromic effect and dipole moment. Stokes shift revealed a bathochromic shift with varying solvent polarity for all molecules which implies π-π*transition. The ground state and excited state dipole moment of the molecules are calculated experimentally using salvatochromic methods like Lippert-Mataga, Bakhshiev, Kawaski-chamma-viallet, and Reichardt's microscopic solvent polarity functions and computationally by density functional theory (DFT) method. It is observed that the excited state dipole moment is higher than the ground state so synthesized molecules are more polar in the excited state than in the ground state. Using the DFT method HOMO and LUMO energy values were obtained and compared with values obtained by the cyclic voltammetry. Using the values of HOMO (highest occupied molecular orbital) and LUMO (lowest unoccupied molecular orbital) we have estimated energy gap, chemical hardness (ɳ), chemical softness (s), ionization potential (IP), electron affinity (EA), electronegativity (χ), electrophilicity (ω), and chemical potential (µ) of the molecules were estimated. The energy gap of MBTC, CBTC, and TBTC were found to be low, that is 3.861 eV, 3.822 eV, and 3.801 eV respectively, this indicates molecules are more reactive and it has the easiest π-π* transition. Further electrophilic and nucleophilic sites were figured out using molecular electrostatic potential (MESP) which is useful in photochemical reactions. Hence the quantum chemical calculation and spectroscopic properties of the molecules can give a better understanding of their use in an optoelectronic device.

Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures From Routine EHRs for Pulmonary Nodule Classification.

The accuracy of predictive models for solitary pulmonary nodule (SPN) diagnosis can be greatly increased by incorporating repeat imaging and medical context, such as electronic health records (EHRs). However, clinically routine modalities such as imaging and diagnostic codes can be asynchronous and irregularly sampled over different time scales which are obstacles to longitudinal multimodal learning. In this work, we propose a transformer-based multimodal strategy to integrate repeat imaging with longitudinal clinical signatures from routinely collected EHRs for SPN classification. We perform unsupervised disentanglement of latent clinical signatures and leverage time-distance scaled self-attention to jointly learn from clinical signatures expressions and chest computed tomography (CT) scans. Our classifier is pretrained on 2,668 scans from a public dataset and 1,149 subjects with longitudinal chest CTs, billing codes, medications, and laboratory tests from EHRs of our home institution. Evaluation on 227 subjects with challenging SPNs revealed a significant AUC improvement over a longitudinal multimodal baseline (0.824 vs 0.752 AUC), as well as improvements over a single cross-section multimodal scenario (0.809 AUC) and a longitudinal imaging-only scenario (0.741 AUC). This work demonstrates significant advantages with a novel approach for co-learning longitudinal imaging and non-imaging phenotypes with transformers. Code available at https://github.com/MASILab/lmsignatures.

COVID-19 and Stroke Trends in A Tertiary Care Center from South India -Our Monsoon Experience.

Introduction: The unprecedented challenges during the COVID pandemic and the subsequent lockdown had resulted in a delay in treatment metrics for acute stroke. There is a rising concern that COVID-19 co-infection can adversely affect stroke outcome. We aim to investigate the impact of COVID-19 in the management of stroke patients. We also compared the differences in stroke manifestations, etiological pattern, treatment course, and outcome of acute stroke patients in COVID-19 confirmed cases. Methodology: A single-center retrospective study was done at the Stroke Unit, Government Medical College, Thiruvananthapuram. Consecutive patients of acute stroke confirmed by imaging, presenting within 24 hours of the onset of symptoms in May to July 2020 and May to July 2019, were included. The primary data variables included baseline demographics, risk factors, admission NIHSS, stroke timings, thrombolysis rate, TOAST etiology, mRS at discharge, and in-hospital mortality. Results: Strokes with higher NIHSS, arrival blood sugar and blood pressure, and delays in door-to-CT and door-to-needle time were more during the pandemic. Intravenous thrombolysis was less and mortality was higher in COVID-19 strokes during the pandemic. COVID-19-positive stroke patients had more hemorrhagic strokes, more severe strokes with low CT ASPECTS, more hemorrhagic transformation, high in-hospital mortality, and poor functional outcome at discharge and 3 months. Conclusion: Our study was a hypothesis-generating study with a limited number of patients. This study has reconfirmed the higher severity of the stroke, with a higher mRS score and mortality during the pandemic, especially among COVID-19-positive stroke patients.

Intravenous cannula induced phlebitis in a tertiary care referral hospital: A prospective observational study with implication from patient's feedback system.

BACKGROUND: Medicines delivered directly to systemic circulation have saved many lives from life-threatening conditions, but also can impart undesirable effects. MATERIALS AND METHODS: A prospective observational study was performed for 10 months in the tertiary care hospital to identify and evaluate cannula induced phlebitis in our study population. The data collection form retrieved demographic details, diseases and cannulation particulars of each patient. Moreover, a patient feedback questionnaire (Cronbach's alpha=0.70) retrieved their concerns toward cannulation. RESULTS: Phlebitis was identified in 96 patients out of 146 subjects enrolled in the study; 52% had the first sign of phlebitis. Female patients were more prone, and the complication occurred irrespective of age (p>0.05). On the other hand, those on IV cefoperazone-sulbactam (n=13, 13.5%) followed by amoxicillin clavulanic acid (n=6, 6%) had significant cannulation complication (p<0.01). The cannula indwells time (p=0.001) and vein assessment (p=0.001) were statistically associated with incidence of phlebitis. Half of our samples had pain lasting about five minutes (χ2=9.2, p<0.05). Nevertheless, limited patients (n = 35, 36.5%) were prescribed topical Heparin Benzyl Nitrate, and none preferred to self-medicate nor opted for other home remedies. CONCLUSIONS: The study depicted high prevalence of phlebitis factored in by poor vein assessment and increase in indwelling time. We recommend proper awareness with on-site skill improvement program for health professionals on administration techniques and monitoring principles in order to lower cannulation related complications.

Newer P2Y12 Inhibitors vs Clopidogrel in Acute Myocardial Infarction With Cardiac Arrest or Cardiogenic Shock: A Systematic Review and Meta-analysis.

OBJECTIVE: To evaluate the outcomes, safety, and efficacy of dual antiplatelet therapy (DAPT) with newer P2Y12 inhibitors compared with clopidogrel in patients with acute myocardial infarction (AMI) complicated by cardiac arrest (CA) or cardiogenic shock (CS). PATIENTS AND METHODS: MEDLINE, EMBASE, and the Cochrane Library were queried systematically from inception to January 2021 for comparative studies of adults (≥18 years) with AMI-CA/CS receiving DAPT with newer P2Y12 inhibitors as opposed to clopidogrel. We compared outcomes (30-day or in-hospital and 1-year all-cause mortality, major bleeding, and definite stent thrombosis) of newer P2Y12 inhibitors and clopidogrel in patients with AMI-CA/CS. RESULTS: Eight studies (1 randomized trial and 7 cohort studies) comprising 1100 patients (695 [63.2%] receiving clopidogrel and 405 [36.8%] receiving ticagrelor or prasugrel) were included. The population was mostly male (68.5%-86.7%). Risk of bias was low for these studies, with between-study heterogeneity and subgroup differences not statistically significant. Compared with the clopidogrel cohort, the newer P2Y12 cohort had lower rates of early mortality (odds ratio [OR], 0.60; 95% CI, 0.45 to 0.81; P=.001) (7 studies) and 1-year mortality (OR, 0.51; 95% CI, 0.36 to 0.71; P<.001) (3 studies). We did not find a significant difference in major bleeding (OR, 1.21; 95% CI, 0.71 to 2.06; P=.48) (6 studies) or definite stent thrombosis (OR, 2.01; 95% CI, 0.63 to 6.45; P=.24) (7 studies). CONCLUSION: In patients with AMI-CA/CS receiving DAPT, compared with clopidogrel, newer P2Y12 inhibitors were associated with lower rates of early and 1-year mortality. Data on major bleeding and stent thrombosis were inconclusive.

SARS-CoV-2 Infection Induces Ferroptosis of Sinoatrial Node Pacemaker Cells.

BACKGROUND: Increasing evidence suggests that cardiac arrhythmias are frequent clinical features of coronavirus disease 2019 (COVID-19). Sinus node damage may lead to bradycardia. However, it is challenging to explore human sinoatrial node (SAN) pathophysiology due to difficulty in isolating and culturing human SAN cells. Embryonic stem cells (ESCs) can be a source to derive human SAN-like pacemaker cells for disease modeling. METHODS: We used both a hamster model and human ESC (hESC)-derived SAN-like pacemaker cells to explore the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the pacemaker cells of the heart. In the hamster model, quantitative real-time polymerase chain reaction and immunostaining were used to detect viral RNA and protein, respectively. We then created a dual knock-in SHOX2:GFP;MYH6:mCherry hESC reporter line to establish a highly efficient strategy to derive functional human SAN-like pacemaker cells, which was further characterized by single-cell RNA sequencing. Following exposure to SARS-CoV-2, quantitative real-time polymerase chain reaction, immunostaining, and RNA sequencing were used to confirm infection and determine the host response of hESC-SAN-like pacemaker cells. Finally, a high content chemical screen was performed to identify drugs that can inhibit SARS-CoV-2 infection, and block SARS-CoV-2-induced ferroptosis. RESULTS: Viral RNA and spike protein were detected in SAN cells in the hearts of infected hamsters. We established an efficient strategy to derive from hESCs functional human SAN-like pacemaker cells, which express pacemaker markers and display SAN-like action potentials. Furthermore, SARS-CoV-2 infection causes dysfunction of human SAN-like pacemaker cells and induces ferroptosis. Two drug candidates, deferoxamine and imatinib, were identified from the high content screen, able to block SARS-CoV-2 infection and infection-associated ferroptosis. CONCLUSIONS: Using a hamster model, we showed that primary pacemaker cells in the heart can be infected by SARS-CoV-2. Infection of hESC-derived functional SAN-like pacemaker cells demonstrates ferroptosis as a potential mechanism for causing cardiac arrhythmias in patients with COVID-19. Finally, we identified candidate drugs that can protect the SAN cells from SARS-CoV-2 infection.

Microbial community composition associated with early developmental stages of the Indian white shrimp, Penaeus indicus.

Gut microbiota is known to influence the physiology, health, nutrient absorption, reproduction, and other metabolic activities of aquatic organisms. Microbial composition can influence intestinal immunity and are considered as health indicators. Information on gut microbial composition provides potential application possibilities to improve shrimp health and production. In the absence of such information for Penaeus indicus, the present study reports the microbial community structure associated with its early developmental stages. Bacterial community associated with the early developmental stages (egg, nauplii, zoea, mysis, PL1, PL6 and PL12) from two hatchery cycles were analysed employing 16S rRNA high throughput sequencing. Proteobacteria and Bacteroidetes, were the two dominant phyla in P. indicus development stages. Sequential sampling revealed the constant change in the bacterial composition at genus level. Alteromonas was dominant in egg and nauplii stage, whilst Ascidiaceihabitans (formerly Roseobacter) was the dominant genera in both PL6 and PL12. The bacterial composition was highly dynamic in early stages and our study suggests that the mysis stage is the critical phase in transforming the microbial composition and it gets stabilised by early post larval stages. This is the first report on the composition of microbiota in early developmental stages of P. indicus. Based on these results the formation of microbial composition seems to be influenced by feeding at early stages. The study provides valuable information to device intervention strategies for healthy seed production.